{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# zipline MeanReversion Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the chapter 04, we introduced `zipline` to simulate the computation of alpha factors from trailing cross-sectional market, fundamental, and alternative data. \n",
    "\n",
    "Now we will exploit the alpha factors to derive and act on buy and sell signals using the custom MeanReversion factor developed in the last chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Zipline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook uses the `conda` environnment `ml4t-zipline`.\n",
    "\n",
    "Please follow the instructions provided [here](../../installation/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:02.074210Z",
     "start_time": "2020-06-17T19:06:02.071580Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:02.956209Z",
     "start_time": "2020-06-17T19:06:02.078907Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pytz import UTC\n",
    "import logbook\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from zipline import run_algorithm\n",
    "from zipline.api import (attach_pipeline, \n",
    "                         date_rules, \n",
    "                         time_rules, \n",
    "                         order_target_percent,\n",
    "                         pipeline_output, \n",
    "                         record, \n",
    "                         schedule_function, \n",
    "                         get_open_orders, \n",
    "                         calendars,\n",
    "                         set_commission, \n",
    "                         set_slippage)\n",
    "from zipline.finance import commission, slippage\n",
    "from zipline.pipeline import Pipeline, CustomFactor\n",
    "from zipline.pipeline.factors import Returns, AverageDollarVolume\n",
    "\n",
    "from pyfolio.utils import extract_rets_pos_txn_from_zipline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:02.959927Z",
     "start_time": "2020-06-17T19:06:02.957599Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logging Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:02.978091Z",
     "start_time": "2020-06-17T19:06:02.961288Z"
    }
   },
   "outputs": [],
   "source": [
    "# setup stdout logging\n",
    "zipline_logging = logbook.NestedSetup([\n",
    "    logbook.NullHandler(level=logbook.DEBUG),\n",
    "    logbook.StreamHandler(sys.stdout, level=logbook.INFO),\n",
    "    logbook.StreamHandler(sys.stderr, level=logbook.ERROR),\n",
    "])\n",
    "zipline_logging.push_application()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algo Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:02.994511Z",
     "start_time": "2020-06-17T19:06:02.979576Z"
    }
   },
   "outputs": [],
   "source": [
    "# Settings\n",
    "MONTH = 21\n",
    "YEAR = 12 * MONTH\n",
    "N_LONGS = 50\n",
    "N_SHORTS = 50\n",
    "VOL_SCREEN = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.016535Z",
     "start_time": "2020-06-17T19:06:03.003055Z"
    }
   },
   "outputs": [],
   "source": [
    "start = pd.Timestamp('2013-01-01', tz=UTC)\n",
    "end = pd.Timestamp('2017-01-01', tz=UTC)\n",
    "capital_base = 1e7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion Factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.039788Z",
     "start_time": "2020-06-17T19:06:03.025622Z"
    }
   },
   "outputs": [],
   "source": [
    "class MeanReversion(CustomFactor):\n",
    "    \"\"\"Compute ratio of latest monthly return to 12m average,\n",
    "       normalized by std dev of monthly returns\"\"\"\n",
    "    inputs = [Returns(window_length=MONTH)]\n",
    "    window_length = YEAR\n",
    "\n",
    "    def compute(self, today, assets, out, monthly_returns):\n",
    "        df = pd.DataFrame(monthly_returns)\n",
    "        out[:] = df.iloc[-1].sub(df.mean()).div(df.std())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Pipeline created by the `compute_factors()` method returns a table with a long and a short column for the 25 stocks with the largest negative and positive deviations of their last monthly return from its annual average, normalized by the standard deviation. It also limited the universe to the 500 stocks with the highest average trading volume over the last 30 trading days. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.049996Z",
     "start_time": "2020-06-17T19:06:03.043177Z"
    }
   },
   "outputs": [],
   "source": [
    "def compute_factors():\n",
    "    \"\"\"Create factor pipeline incl. mean reversion,\n",
    "        filtered by 30d Dollar Volume; capture factor ranks\"\"\"\n",
    "    mean_reversion = MeanReversion()\n",
    "    dollar_volume = AverageDollarVolume(window_length=30)\n",
    "    return Pipeline(columns={'longs'  : mean_reversion.bottom(N_LONGS),\n",
    "                             'shorts' : mean_reversion.top(N_SHORTS),\n",
    "                             'ranking': mean_reversion.rank(ascending=False)},\n",
    "                    screen=dollar_volume.top(VOL_SCREEN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before_trading_start() ensures the daily execution of the pipeline and the recording of the results, including the current prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.058172Z",
     "start_time": "2020-06-17T19:06:03.051602Z"
    }
   },
   "outputs": [],
   "source": [
    "def before_trading_start(context, data):\n",
    "    \"\"\"Run factor pipeline\"\"\"\n",
    "    context.factor_data = pipeline_output('factor_pipeline')\n",
    "    record(factor_data=context.factor_data.ranking)\n",
    "    assets = context.factor_data.index\n",
    "    record(prices=data.current(assets, 'price'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Rebalancing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The new rebalance() method submits trade orders to the exec_trades() method for the assets flagged for long and short positions by the pipeline with equal positive and negative weights. It also divests any current holdings that are no longer included in the factor signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.066792Z",
     "start_time": "2020-06-17T19:06:03.059522Z"
    }
   },
   "outputs": [],
   "source": [
    "def rebalance(context, data):\n",
    "    \"\"\"Compute long, short and obsolete holdings; place trade orders\"\"\"\n",
    "    factor_data = context.factor_data\n",
    "    assets = factor_data.index\n",
    "\n",
    "    longs = assets[factor_data.longs]\n",
    "    shorts = assets[factor_data.shorts]\n",
    "    divest = context.portfolio.positions.keys() - longs.union(shorts)\n",
    "\n",
    "    exec_trades(data, assets=divest, target_percent=0)\n",
    "    exec_trades(data, assets=longs, target_percent=1 / N_LONGS if N_LONGS else 0)\n",
    "    exec_trades(data, assets=shorts, target_percent=-1 / N_SHORTS if N_SHORTS else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.078261Z",
     "start_time": "2020-06-17T19:06:03.068431Z"
    }
   },
   "outputs": [],
   "source": [
    "def exec_trades(data, assets, target_percent):\n",
    "    \"\"\"Place orders for assets using target portfolio percentage\"\"\"\n",
    "    for asset in assets:\n",
    "        if data.can_trade(asset) and not get_open_orders(asset):\n",
    "            order_target_percent(asset, target_percent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `rebalance()` method runs according to `date_rules` and `time_rules` set by the `schedule_function()` utility at the beginning of the week, right after market_open as stipulated by the built-in US_EQUITIES calendar (see docs for details on rules). \n",
    "\n",
    "You can also specify a trade commission both in relative terms and as a minimum amount. There is also an option to define slippage, which is the cost of an adverse change in price between trade decision and execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:03.086824Z",
     "start_time": "2020-06-17T19:06:03.079400Z"
    }
   },
   "outputs": [],
   "source": [
    "def initialize(context):\n",
    "    \"\"\"Setup: register pipeline, schedule rebalancing,\n",
    "        and set trading params\"\"\"\n",
    "    attach_pipeline(compute_factors(), 'factor_pipeline')\n",
    "    schedule_function(rebalance,\n",
    "                      date_rules.week_start(),\n",
    "                      time_rules.market_open(),\n",
    "                      calendar=calendars.US_EQUITIES)\n",
    "\n",
    "    set_commission(us_equities=commission.PerShare(cost=0.00075, min_trade_cost=.01))\n",
    "    set_slippage(us_equities=slippage.VolumeShareSlippage(volume_limit=0.0025, price_impact=0.01))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The algorithm executes upon calling the run_algorithm() function and returns the backtest performance DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:07:11.878690Z",
     "start_time": "2020-06-17T19:06:03.088021Z"
    },
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2020-06-17 19:06:03.303387] INFO: Loader: Cache at /home/stefan/.zipline/data/SPY_benchmark.csv does not have data from 1990-01-02 00:00:00+00:00 to 2020-06-17 00:00:00+00:00.\n",
      "\n",
      "[2020-06-17 19:06:03.303993] INFO: Loader: Downloading benchmark data for 'SPY' from 1989-12-29 00:00:00+00:00 to 2020-06-17 00:00:00+00:00\n",
      "[2020-06-17 19:06:04.488835] WARNING: Loader: Still don't have expected benchmark data for 'SPY' from 1989-12-29 00:00:00+00:00 to 2020-06-17 00:00:00+00:00 after redownload!\n",
      "[2020-06-17 19:06:04.513370] INFO: Loader: Cache at /home/stefan/.zipline/data/treasury_curves.csv does not have data from 1990-01-02 00:00:00+00:00 to 2020-06-17 00:00:00+00:00.\n",
      "\n",
      "[2020-06-17 19:06:04.513789] INFO: Loader: Downloading treasury data for 'SPY' from 1990-01-02 00:00:00+00:00 to 2020-06-17 00:00:00+00:00\n",
      "[2020-06-17 19:06:05.204009] WARNING: Loader: Still don't have expected treasury data for 'SPY' from 1990-01-02 00:00:00+00:00 to 2020-06-17 00:00:00+00:00 after redownload!\n",
      "[2020-06-17 19:06:53.536705] INFO: Performance: after split: asset: Equity(406 [BOFI]), amount: 1768, cost_basis: 23.84, last_sale_price: 83.29\n",
      "[2020-06-17 19:06:53.537293] INFO: Performance: returning cash: 0.0\n",
      "[2020-06-17 19:07:11.857542] INFO: zipline.finance.metrics.tracker: Simulated 1008 trading days\n",
      "first open: 2013-01-02 14:31:00+00:00\n",
      "last close: 2016-12-30 21:00:00+00:00\n"
     ]
    }
   ],
   "source": [
    "backtest = run_algorithm(start=start,\n",
    "                         end=end,\n",
    "                         initialize=initialize,\n",
    "                         before_trading_start=before_trading_start,\n",
    "                         capital_base=capital_base)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract pyfolio Inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `extract_rets_pos_txn_from_zipline` utility provided by `pyfolio` extracts the data used to compute performance metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:07:50.398545Z",
     "start_time": "2020-06-17T19:07:49.276585Z"
    }
   },
   "outputs": [],
   "source": [
    "returns, positions, transactions = extract_rets_pos_txn_from_zipline(backtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist Results for use with `pyfolio`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:07:59.315120Z",
     "start_time": "2020-06-17T19:07:58.873075Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    store.put('backtest/equal_weight', backtest)\n",
    "    store.put('returns/equal_weight', returns)\n",
    "    store.put('positions/equal_weight', positions)\n",
    "    store.put('transactions/equal_weight', transactions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:08:00.515977Z",
     "start_time": "2020-06-17T19:08:00.177915Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes= plt.subplots(nrows=2, figsize=(14,6))\n",
    "returns.add(1).cumprod().sub(1).plot(ax=axes[0], title='Cumulative Returns')\n",
    "transactions.groupby(transactions.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1], title='Cumulative Transactions')\n",
    "fig.tight_layout()\n",
    "sns.despine();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "positions.index = positions.index.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:08:20.660331Z",
     "start_time": "2020-06-17T19:08:18.394556Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 8))\n",
    "sns.heatmap(positions.replace(0, np.nan).dropna(how='all', axis=1).T, \n",
    "            cmap=sns.diverging_palette(h_neg=20, h_pos=200), ax=ax, center=0);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:08:28.123075Z",
     "start_time": "2020-06-17T19:08:28.094872Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sid</th>\n",
       "      <th>Equity(0 [A])</th>\n",
       "      <th>Equity(1 [AA])</th>\n",
       "      <th>Equity(2 [AAL])</th>\n",
       "      <th>Equity(4 [AAN])</th>\n",
       "      <th>Equity(7 [AAP])</th>\n",
       "      <th>Equity(8 [AAPL])</th>\n",
       "      <th>Equity(12 [ABBV])</th>\n",
       "      <th>Equity(13 [ABC])</th>\n",
       "      <th>Equity(17 [ABG])</th>\n",
       "      <th>Equity(19 [ABMD])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(3172 [YHOO])</th>\n",
       "      <th>Equity(3175 [YUM])</th>\n",
       "      <th>Equity(3177 [Z])</th>\n",
       "      <th>Equity(3180 [ZBH])</th>\n",
       "      <th>Equity(3181 [ZBRA])</th>\n",
       "      <th>Equity(3189 [ZIOP])</th>\n",
       "      <th>Equity(3194 [ZNGA])</th>\n",
       "      <th>Equity(3195 [ZOES])</th>\n",
       "      <th>Equity(3197 [ZTS])</th>\n",
       "      <th>cash</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-08</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.961259e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-09</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.631190e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-10</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.425350e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-11</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.388467e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-14</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.362620e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 1375 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sid         Equity(0 [A])  Equity(1 [AA])  Equity(2 [AAL])  Equity(4 [AAN])  Equity(7 [AAP])  Equity(8 [AAPL])  Equity(12 [ABBV])  Equity(13 [ABC])  Equity(17 [ABG])  Equity(19 [ABMD])      ...       Equity(3172 [YHOO])  Equity(3175 [YUM])  Equity(3177 [Z])  Equity(3180 [ZBH])  Equity(3181 [ZBRA])  Equity(3189 [ZIOP])  Equity(3194 [ZNGA])  Equity(3195 [ZOES])  Equity(3197 [ZTS])          cash\n",
       "2013-01-08            0.0             0.0              0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0      ...                       0.0                 0.0               0.0                 0.0                  0.0                  0.0                  0.0                  0.0                 0.0  7.961259e+06\n",
       "2013-01-09            0.0             0.0              0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0      ...                       0.0                 0.0               0.0                 0.0                  0.0                  0.0                  0.0                  0.0                 0.0  7.631190e+06\n",
       "2013-01-10            0.0             0.0              0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0      ...                       0.0                 0.0               0.0                 0.0                  0.0                  0.0                  0.0                  0.0                 0.0  7.425350e+06\n",
       "2013-01-11            0.0             0.0              0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0      ...                       0.0                 0.0               0.0                 0.0                  0.0                  0.0                  0.0                  0.0                 0.0  7.388467e+06\n",
       "2013-01-14            0.0             0.0              0.0              0.0              0.0               0.0                0.0               0.0               0.0                0.0      ...                       0.0                 0.0               0.0                 0.0                  0.0                  0.0                  0.0                  0.0                 0.0  7.362620e+06\n",
       "\n",
       "[5 rows x 1375 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "positions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:08:28.390678Z",
     "start_time": "2020-06-17T19:08:28.381970Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 19452 entries, 2013-01-08 21:00:00+00:00 to 2016-12-30 21:00:00+00:00\n",
      "Data columns (total 8 columns):\n",
      "amount         19452 non-null int64\n",
      "commission     0 non-null object\n",
      "dt             19452 non-null datetime64[ns, UTC]\n",
      "order_id       19444 non-null object\n",
      "price          19452 non-null float64\n",
      "sid            19452 non-null object\n",
      "symbol         19452 non-null object\n",
      "txn_dollars    19452 non-null float64\n",
      "dtypes: datetime64[ns, UTC](1), float64(2), int64(1), object(4)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "transactions.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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